emlearn
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| emlearn | snipp.in | |
|---|---|---|
| 5 | 5 | |
| 378 | 235 | |
| 7.2% | - | |
| 9.2 | 3.8 | |
| 24 days ago | 7 days ago | |
| Python | Vue | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
emlearn
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EleutherAI announces it has become a non-profit
> My big gripe, and for obvious reasons, is that we need to step away from cloud-based inference, and it doesn't seem like anyone's working on that.
I think there are steps being taken in this direction (check out [1] and [2] for interesting lightweight transpile / ad-hoc training projects) but there is a lack of centralized community for these constrained problems.
[1] https://github.com/emlearn/emlearn
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Simple and embedded friendly C code for Machine Learning inference algorithms
Examples: Gaussian Mixture Models (GMM) for anomaly detection or clustering Mahalanobis distance (EllipticEnvelope) for anomaly detection Decision trees and tree ensembles (Random Forest, ExtraTrees) Feed-forward Neural Networks (Multilayer Perceptron, MLP) for classification Gaussian Naive Bayes for classification
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[D] Drop your best open source Deep learning related Project
https://github.com/emlearn/emlearn is a ML inference engine for microcontrollers and embedded systems, allowing to deploy models to any platform with a C99 compiler. Has also been used for network traffic analysis as a Linux kernel module, and embedded in Android apps.
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Regression with the C64
The C64 has 64 kB of RAM. That is more than many contemporary microcontrollers. Using something like https://github.com/emlearn/emlearn allows to generate portable C code of ML models for such targets. Should be able to classify digits (MNIST) no problem on such hardware. Assuming there is a workable C compiler available.
Disclosure: Maintainer of emlearn project.
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Ask HN: What are some tools / libraries you built yourself?
I built emlearn, a Machine Learning inference engine for microcontrollers and embedded systems. It allows converting traditional ML models to simple and portable C99, following best practices in embedded software (no dynamic allocations etc). https://github.com/emlearn/emlearn
snipp.in
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Ask HN: What are some tools / libraries you built yourself?
I built https://snipp.in because I was top frustrated about the loading times of notion. I am a developer and I take notes quite often, most of us spend a lot of time on an IDE and when we need format a quick json or copy a tiny snippet we often find ourselves in opening another instance of an editor with a txt file or random website to formate json. Snipp.in is a tiny jn browser editor, note taking app and a snippet manager all in one which looks like an Editor but really fast without any bs of signin/signups or cloud. It just stores everything in your browser using IndexedDB. It's also open-sourced at https://github.com/haxzie/snipp.in
- SnippIn - Develoepr friendly, Lite Weight, fast, in browser notes and code snippet manager built with Vue.js, Monaco and Dexie
- I made a developer friendly, in browser, lite weight notes and code snippet manager using Vue.js, Monaco and Dexie
- I made an in browser notes and snippet manager using Vue.js, Monaco and Dexie
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